Evidence map›Paper›PMID 34268333›Full record

ArticleFrontiers in molecular biosciences2021

Structural and Biophysical Investigation of the Key Hotspots on the Surface of Epstein-Barr Nuclear Antigen 1 Essential for DNA Recognition and Pathogenesis.

Huma Farooque Hashmi, Muhammad Waseem, Syed Shujait Ali, Zahid Hussain, Kaoshan Chen

Open access · goldAbstract read
In one paragraph

Article in Frontiers in molecular biosciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 90% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 2 countries.

Huma Farooque HashmiCollege of Life Sciences, Shandong University, Jinan, China.
Muhammad WaseemFaculty of Rehabilitation and Allied Health Science, Riphah International University, Islamabad, Pakistan.
Syed Shujait AliCenter for Biotechnology and Microbiology, University of Swat, Swat, Pakistan.
Zahid HussainCenter for Biotechnology and Microbiology, University of Swat, Swat, Pakistan.
Kaoshan ChenCollege of Life Sciences, Shandong University, Jinan, China.
Shandong University · CNUniversity of Swat · PKRiphah International University · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epstein-Barr Virus (EBV) is considered the most important human pathogen due to its role in infections and cellular malignancies. It has been reported that this Oncolytic virus infects 90% world's population. EBNA1 is required for DNA binding and survival of the virus and is considered an essential drug target. The biochemical and structural properties of this protein are known, but it is still unclear which residues impart a critical role in the recognition of dsDNA. Intending to disclose only the essential residues in recognition of dsDNA, this study used a computational pipeline to generate an alanine mutant of each interacting residue and determine the impact on the binding. Our analysis revealed that R469A, K514A, Y518A, R521A and R522A are the key hotspots for the recognition of dsDNA by the EBNA1. The dynamics properties, i.e. stability, flexibility, structural compactness, hydrogen bonding frequency, binding affinity, are altered by disrupting the protein-DNA contacts, thereby decreases the binding affinity. In particular, the two arginine substitution, R521A and R522A, significantly affected the total binding energy. Thus, we hypothesize that these residues impart a critical role in the dsDNA recognition and pathogenesis. This study would help to design structure-based drugs against the EBV infections.

Indexed as

DNA recognitionEBNA1free energy calculationsin silico mutagenesisMD simulation

Identifiers

PMID34268333
PMCPMC8275655
OpenAlexW3175751098

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.